Snowflake ML Functions include Top Insights, which performs key-driver analysis to explain why a business metric changed. It can compare groups or time periods and rank dimensions that contributed most strongly to a result. Snowflake documentation uses the example of identifying locations, salespeople, customers, verticals, and other factors responsible for a recent revenue shortfall. A department can be evaluated as one of those dimensions, allowing the analysis to identify which department contributed to the decline. Snowpark is a developer framework for processing data with languages such as Python, Java, and Scala. Snowpipe loads files continuously, while AI_EXTRACT extracts structured information from documents. Those features do not directly perform the requested driver analysis. Therefore, ML Functions is the correct answer.